Kerry Back
We’ll use random forests.
from sklearn.ensemble import RandomForestRegressor X = data[["roeq", "mom12m"]] y = data["rnk"] model = RandomForestRegressor( max_depth=4, random_state=0 ) model.fit(X,y)
R-squared
model.score(X,y)
0.15523747125534115
Importance of features
model.feature_importances_
array([0.59382638, 0.40617362])
Make a prediction
import numpy as np x = np.array([.1, .4]).reshape(1,2) model.predict(x)
array([0.55933904])
from joblib import dump, load dump(model, "forest1.joblib")
forest = load("forest1.joblib") forest.predict(x)